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Efficient FP-Growth Distributed Algorithm with Minimum Communication Overhead

  • Unique Paper ID: 142417
  • Volume: 2
  • Issue: 1
  • PageNo: 142-147
  • Abstract:
  • Currently, organizations are distributed geographically normally;“all the sites locally store its day-to-day data, which is as a result of updated. Centralized statement mining algorithms can’t be used in a well known type of organizations for discovering convenient patterns as merging of announcement sets from contradictory sites is not efficient as lightly as it causes rich network package costs. Data mining in abstracted consist of has convert an perceptive sub-domain of announcement mining research. In distributed association menace mining algorithm, such of the practice challenges is to made a long story short the package overhead. Data sites are forced upon to squabble lot of flea in ear in the word mining behavior which manage generates package overhead. This declares proposes an association intimidate mining algorithm minimize communication overhead among all the participating disclosure sites. Instead of transmitting bodily item sets and their counts, the algorithm transmits a as much again vector of frequently no end in sight item sets by Message Passing Interface (MPI) technique. Another contest is to cut number of database survey and motivate the frequent item sets of database.So the algorithm term as “EfficientFP-Growth Distributed Algorithm” is proposed. This algorithm reduces time of scan of partition database that increases the overall performance of the algorithm
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 2
  • Issue: 1
  • PageNo: 142-147

Efficient FP-Growth Distributed Algorithm with Minimum Communication Overhead

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Impact Factor
8.01 (Year 2024)
UGC Approved
Journal no 47859

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